relationship between exam marks and study hours. If all students’ marks are increased by 10 (for example the original mark is 70, and the new mark is 80). The change in marking may affect the regression results. slope would change TRUE FALSE Standard error of the slope (1) would change TRUE FALSE t-statistic of the slope (B1) would change TRUE FALSE P-value for the slope B1) would change TRUE FALSE 95% confidence interval forB1 would change TRUE FALSE
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
relationship between exam marks and study hours. If all students’ marks are increased by 10 (for example the original mark is 70, and the new mark is 80). The change in marking may affect the regression results.
slope would change TRUE FALSE
Standard error of the slope (1) would change TRUE FALSE
t-statistic of the slope (B1) would change TRUE FALSE
P-value for the slope B1) would change TRUE FALSE
95% confidence interval forB1 would change TRUE FALSE
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